IEEE

A Novel Classification Framework Using the Graph Representations of Electroencephalogram for Motor Imagery Based Brain-Computer Interface

Abstract: The motor imagery (MI) based brain-computer interfaces (BCIs) have been proposed as a potential physical rehabilitation technology. However, the low classification accuracy achievable with ...
IEEE

Graph Convolution Neural Network Based End-to-End Channel Selection and Classification for Motor Imagery Brain–Computer Interfaces

Abstract: Classification of electroencephalogram-based motor imagery (MI-EEG) tasks is crucial in brain–computer interface (BCI). EEG signals require a large number of channels in the acquisition ...